DevOps Engineers in Munich

• Built and operated an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, and Autoformer).
• Implemented CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform) and data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) to training and evaluation, model registry, and endpoint deployment.
• Integrated MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
• Developed and containerized PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
• Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), centralized logging, and cost monitoring.
• Automated infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connected to existing market data systems and event pipelines.
• Migrated existing workloads and databases (IONOS → Azure, MongoDB) and integrated them into central MLOps workflows and internal networks.
• Extended the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
• Analyzed and designed a software solution to efficiently process large volumes of data (>3000 messages/sec) (market data store).
• Developed Spring Boot / Java 21 container services with RabbitMQ to distribute exchange data through MongoDB (Kubernetes), with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
• Integrated RESTHeart to create a REST API for MongoDB.
• Built an Angular frontend to simplify data queries and master data maintenance.
• Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
• Developed Python scripts to transform and clean incoming exchange data (Pandas, scikit-learn).

• Adjusting, optimizing, configuring, and administering a multi-stage GitLab instance with over 250 users
• Building, adjusting, expanding, and optimizing infrastructure, configuration, and monitoring
• Providing services and handing them over to production
• System environment: DependencyTrack, GitLab, Grafana, Hedgedoc, Kubernetes, OAuth2 Proxy, Openstack, Prometheus, Syseleven

• Building an independent enterprise IT setup — cloud strategy, network, AWS landing zone, security requirements, contract negotiations.
• Migration of all applications; avoiding high contractual penalties for the client.
• Onboarding and coordination o...

• Responsible for Openshift/Kubernetes on-prem administration and developer support.
• Developed URP infrastructure automation with Python, Ansible, Kustomize and ArgoCD, Argo Workflow/Events stack.
• Wrote smoke and load tests for URP infrastructure utilizing Python, Kustomize and ApplicationSets.
• Helped to set up and deploy URP infrastructure in Google Cloud, GKE.
• Set up monitoring for URP and ArgoCD stack with Splunk Cloud.
• Performed system administration tasks across RedHat Linux, Kubernetes/Openshift, ArgoCD, GitLab, Bitbucket Enterprise, Kafka and MongoDB.

• Guided a large-scale agile transformation, improving team agility, DevOps adoption, and cloud readiness.
• Supported DevOps & CI/CD practices to optimize cloud deployment strategies and reduce time-to-market.
• Led agile coaching initiatives to enhance cross-functional collaboration between IT and business teams.
• designed agile governance structures to align executive leadership with cloud and digital transformation goals.
• Technologies & Frameworks: Agile (Scrum, SAFe), DevOps, Cloud Adoption, IT Governance, CI/CD, Change Management

• Maintained a SaaS billing platform on AWS as part of the Site Reliability Engineering (SRE) team.
• Played a key role in an AWS cloud migration project, implementing Terraform (IaC), creating CI/CD processes and pipelines, hardening images, upgrading tool versions, and developing scripts.
• Wrote documentation.

AWS Cloud migration:

• Design and implement CI/CD for deploying AWS resources using GitLab CI, Terraform, and GitOps.
• Create and configure DevOps toolchain including Jenkins, Harbor, and Vault.
• Deploy billing application, microservices, and supporting infrastructure services to Nomad clusters.
• Re-designed TLS/mTLS certificate management using Vault and Lambda.

Security (Infrastructure Hardening & Patch Management & Vulnerability Scanning):

• Managed multiple AWS accounts for Consul/Nomad/Traefik clusters (10–20 EC2 instances/account, ASG) and DevOps toolchain accounts (Harbor, Jenkins, Vault).
• Created hardened AMIs via Packer based on CIS benchmarks for Nomad, Jenkins, Harbor, and Vault; deployed using Terraform.
• Integrated Trivy via Harbor plugin for container image scanning.
• Implemented strict AWS VPC security group rules.
• Developed and maintained patching process across environments using Qualys and Wiz.
• Deployed Qualys Cloud Agent to all EC2 instances, tracked CVEs and tested patches in lower environments before rollout.
• Automated patch deployment across all AWS accounts using Terraform and GitLab CI and verified patch compliance via Qualys/Wiz dashboards.

• Worked as freelance Senior DevOps Consultant on-site for IBM at a European Union Agency, operating in a highly secure, air-gapped environment managing classified systems.
• Led automation and DevOps initiatives for a large-scale OpenShift platform (>400 nodes), driving deployment efficiency, GitOps adoption, and operational automation using Ansible, Python, and Bash while ensuring compliance with security requirements.
• Spearheaded automation of release and deployment workflows in a private cloud environment hosting 400+ OpenShift nodes, significantly improving deployment speed and reliability.
• Migrated existing playbooks, roles, and templates from Ansible Tower to Ansible Automation Platform (AAP), ensuring full compliance with fully-qualified collection names (FQCN) and preparing custom Execution Environments (EE) for containerized automation.
• Implemented GitOps Agent for AAP Controller Configuration as Code, enabling automated synchronization (CRUD) of Ansible Controller objects based on repository-stored configuration definitions using GitHub webhooks.
• Designed and automated complex multi-step operational workflows including environment cleanup, Helix cluster component re-creation, Kafka topic management, and OpenShift object lifecycle management across ~100 environments.
• Achieved a reduction of multi-day manual operations to under a few hours through automation improvements spanning multiple AAP clusters and OpenShift environments.
• Integrated Ansible Automation Platform with Thycotic (Delinea) Secret Server via lookup plugin to enhance secure credential management in automated processes.
• Managed deployment tasks, platform troubleshooting, and Istio network configurations while adhering to stringent EU PSC security and compliance standards.
• Collaborated with infrastructure and application teams to refine deployment procedures, develop naming conventions, and continuously improve automation coverage in an air-gapped, classified environment.

• Further development of the internal "ECockpit" platform with an Angular 17 frontend and .NET (C#) backend
• Maintenance and further development of Azure DevOps pipelines
• Introduction of technical improvements in build & release processes
• Collaboration on a modular architecture approach (Clean Architecture & DDD)
• Focus on scalability and secure data processing
• Tech stack: Angular 17, .NET / C#, Azure, Azure DevOps, Git, CI/CD, Clean Architecture, Domain Driven Design

• Developed dynamic web components for displaying KPIs, intelligent map applications, and operational process analysis tools
• Angular 18+
• Leaflet, MapLibre
• NestJS, JavaScript, HTML, CSS
• PostgreSQL, GraphQL, RabbitMQ
• Gitea, Jenkins, Docker

• Architected and implemented an enterprise-grade AI Agent Platform leveraging Retrieval Augmented Generation (RAG) architecture to enhance clinical data insights.
• Established robust CI/CD pipelines for LLM applications using CDK and Jenkins, significantly reducing deployment times.
• Implemented comprehensive observability solutions that increased agent reliability across pharmaceutical environments.
• Designed scalable AI workflows with advanced orchestration that optimized context handling for enterprise data sources.
• Technologies: AI Agents (LangChain, LangGraph, Bedrock, Smolagents, Streamlit); LLM Operations (Tracing, Testing, Evaluation, LangSmith, LangFuse); Infrastructure-As-Code (AWS CDK, Terraform, Typescript, Jenkins); Vectors, Embeddings, RAG (OpenSearch, pgvector, PDF Extraction)

• Operations and extensions of Azure DevOps pipelines

• Operations and extensions of AWS services

• Citrix (Windows 10, Bitwarden)

• AWS: ECR, EKS, CloudFront CDN, Route 53, VPC peering and CNI upgrade, Atlas MongoDB, S3 buckets, static website hosting

• Azure: build and deploy with DevOps pipelines

• Migration of a mainframe application (PL/1, zOS) to the cloud (Azure)
• Data transfer from z/OS (USS) to Azure storage (blob containers, file shares)
• Implementation of the mainframe job control in Java
• Mapping of job network dependencies in Control-M
• Performance analysis and optimization measures
• DB2 (z/OS) migration to Postgres (Azure)
• Technologies: Azure (storage, VM, VMSS, Postgres), z/OS (USS), DB2, Postgres, Packer, Terraform, Docker, Jenkins, GitHub Actions, Control-M
• Tools: Eclipse, Visual Studio Code, IntelliJ

• Specialized in cloud infrastructure design, optimizing AWS and SaaS usage.
• Empowered development teams by ensuring security, scalability and reliability.
• Expertise included robust monitoring and automation for streamlined deployments.
• Provided technical guidance for faster releases and supported microservices principles.
• Actively participated in architecture discussions and shared critical infrastructure knowledge with development teams.

• JEE Software Engineer
• DevOps Engineer
• Java, JEE, JBoss/WildFly, Vaadin, CI/CD Pipelines, Jenkins, Maven, Git, Oracle database, MSSQL Server database